{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 共享单车数据探索\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入必要的工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O\n",
    "\n",
    "from sklearn.metrics import r2_score  #评价回归预测模型的性能\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "#color = sns.color_palette()\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# path to where the data lies\n",
    "#dpath = './'\n",
    "data = pd.read_csv(\"day.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据基本信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.5+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "instant       0\n",
       "dteday        0\n",
       "season        0\n",
       "yr            0\n",
       "mnth          0\n",
       "holiday       0\n",
       "weekday       0\n",
       "workingday    0\n",
       "weathersit    0\n",
       "temp          0\n",
       "atemp         0\n",
       "hum           0\n",
       "windspeed     0\n",
       "casual        0\n",
       "registered    0\n",
       "cnt           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 293,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### 查看是否有空值\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 探索数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "此处得到各属性的样本数目、均值、标准差、最小值、1/4分位数（25%）、中位数（50%）、3/4分位数（75%）、最大值\n",
    "可初步了解各特征的分布"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.204348</td>\n",
       "      <td>0.233209</td>\n",
       "      <td>0.518261</td>\n",
       "      <td>0.089565</td>\n",
       "      <td>1606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.196522</td>\n",
       "      <td>0.208839</td>\n",
       "      <td>0.498696</td>\n",
       "      <td>0.168726</td>\n",
       "      <td>1510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.165000</td>\n",
       "      <td>0.162254</td>\n",
       "      <td>0.535833</td>\n",
       "      <td>0.266804</td>\n",
       "      <td>959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.138333</td>\n",
       "      <td>0.116175</td>\n",
       "      <td>0.434167</td>\n",
       "      <td>0.361950</td>\n",
       "      <td>822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.150833</td>\n",
       "      <td>0.150888</td>\n",
       "      <td>0.482917</td>\n",
       "      <td>0.223267</td>\n",
       "      <td>1321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.169091</td>\n",
       "      <td>0.191464</td>\n",
       "      <td>0.686364</td>\n",
       "      <td>0.122132</td>\n",
       "      <td>1263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.172727</td>\n",
       "      <td>0.160473</td>\n",
       "      <td>0.599545</td>\n",
       "      <td>0.304627</td>\n",
       "      <td>1162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.165000</td>\n",
       "      <td>0.150883</td>\n",
       "      <td>0.470417</td>\n",
       "      <td>0.301000</td>\n",
       "      <td>1406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.160870</td>\n",
       "      <td>0.188413</td>\n",
       "      <td>0.537826</td>\n",
       "      <td>0.126548</td>\n",
       "      <td>1421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.233333</td>\n",
       "      <td>0.248112</td>\n",
       "      <td>0.498750</td>\n",
       "      <td>0.157963</td>\n",
       "      <td>1248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.231667</td>\n",
       "      <td>0.234217</td>\n",
       "      <td>0.483750</td>\n",
       "      <td>0.188433</td>\n",
       "      <td>1204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.175833</td>\n",
       "      <td>0.176771</td>\n",
       "      <td>0.537500</td>\n",
       "      <td>0.194017</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.216667</td>\n",
       "      <td>0.232333</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.146775</td>\n",
       "      <td>683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.292174</td>\n",
       "      <td>0.298422</td>\n",
       "      <td>0.741739</td>\n",
       "      <td>0.208317</td>\n",
       "      <td>1650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.261667</td>\n",
       "      <td>0.255050</td>\n",
       "      <td>0.538333</td>\n",
       "      <td>0.195904</td>\n",
       "      <td>1927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.177500</td>\n",
       "      <td>0.157833</td>\n",
       "      <td>0.457083</td>\n",
       "      <td>0.353242</td>\n",
       "      <td>1543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.171970</td>\n",
       "      <td>981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.096522</td>\n",
       "      <td>0.098839</td>\n",
       "      <td>0.436522</td>\n",
       "      <td>0.246600</td>\n",
       "      <td>986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.097391</td>\n",
       "      <td>0.117930</td>\n",
       "      <td>0.491739</td>\n",
       "      <td>0.158330</td>\n",
       "      <td>1416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.223478</td>\n",
       "      <td>0.234526</td>\n",
       "      <td>0.616957</td>\n",
       "      <td>0.129796</td>\n",
       "      <td>1985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.217500</td>\n",
       "      <td>0.203600</td>\n",
       "      <td>0.862500</td>\n",
       "      <td>0.293850</td>\n",
       "      <td>506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.195000</td>\n",
       "      <td>0.219700</td>\n",
       "      <td>0.687500</td>\n",
       "      <td>0.113837</td>\n",
       "      <td>431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.203478</td>\n",
       "      <td>0.223317</td>\n",
       "      <td>0.793043</td>\n",
       "      <td>0.123300</td>\n",
       "      <td>1167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196522</td>\n",
       "      <td>0.212126</td>\n",
       "      <td>0.651739</td>\n",
       "      <td>0.145365</td>\n",
       "      <td>1098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.216522</td>\n",
       "      <td>0.250322</td>\n",
       "      <td>0.722174</td>\n",
       "      <td>0.073983</td>\n",
       "      <td>1096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>702</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.347500</td>\n",
       "      <td>0.359208</td>\n",
       "      <td>0.823333</td>\n",
       "      <td>0.124379</td>\n",
       "      <td>4649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>702</th>\n",
       "      <td>703</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.452500</td>\n",
       "      <td>0.455796</td>\n",
       "      <td>0.767500</td>\n",
       "      <td>0.082721</td>\n",
       "      <td>6234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>704</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.475833</td>\n",
       "      <td>0.469054</td>\n",
       "      <td>0.733750</td>\n",
       "      <td>0.174129</td>\n",
       "      <td>6606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>704</th>\n",
       "      <td>705</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.438333</td>\n",
       "      <td>0.428012</td>\n",
       "      <td>0.485000</td>\n",
       "      <td>0.324021</td>\n",
       "      <td>5729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>706</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.255833</td>\n",
       "      <td>0.258204</td>\n",
       "      <td>0.508750</td>\n",
       "      <td>0.174754</td>\n",
       "      <td>5375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>706</th>\n",
       "      <td>707</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.320833</td>\n",
       "      <td>0.321958</td>\n",
       "      <td>0.764167</td>\n",
       "      <td>0.130600</td>\n",
       "      <td>5008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707</th>\n",
       "      <td>708</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.381667</td>\n",
       "      <td>0.389508</td>\n",
       "      <td>0.911250</td>\n",
       "      <td>0.101379</td>\n",
       "      <td>5582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>708</th>\n",
       "      <td>709</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.384167</td>\n",
       "      <td>0.390146</td>\n",
       "      <td>0.905417</td>\n",
       "      <td>0.157975</td>\n",
       "      <td>3228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709</th>\n",
       "      <td>710</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.435833</td>\n",
       "      <td>0.435575</td>\n",
       "      <td>0.925000</td>\n",
       "      <td>0.190308</td>\n",
       "      <td>5170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>711</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.353333</td>\n",
       "      <td>0.338363</td>\n",
       "      <td>0.596667</td>\n",
       "      <td>0.296037</td>\n",
       "      <td>5501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>711</th>\n",
       "      <td>712</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.297500</td>\n",
       "      <td>0.297338</td>\n",
       "      <td>0.538333</td>\n",
       "      <td>0.162937</td>\n",
       "      <td>5319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>712</th>\n",
       "      <td>713</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.295833</td>\n",
       "      <td>0.294188</td>\n",
       "      <td>0.485833</td>\n",
       "      <td>0.174129</td>\n",
       "      <td>5532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>713</th>\n",
       "      <td>714</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.281667</td>\n",
       "      <td>0.294192</td>\n",
       "      <td>0.642917</td>\n",
       "      <td>0.131229</td>\n",
       "      <td>5611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>714</th>\n",
       "      <td>715</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.324167</td>\n",
       "      <td>0.338383</td>\n",
       "      <td>0.650417</td>\n",
       "      <td>0.106350</td>\n",
       "      <td>5047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>715</th>\n",
       "      <td>716</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.362500</td>\n",
       "      <td>0.369938</td>\n",
       "      <td>0.838750</td>\n",
       "      <td>0.100742</td>\n",
       "      <td>3786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>716</th>\n",
       "      <td>717</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.393333</td>\n",
       "      <td>0.401500</td>\n",
       "      <td>0.907083</td>\n",
       "      <td>0.098258</td>\n",
       "      <td>4585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717</th>\n",
       "      <td>718</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.410833</td>\n",
       "      <td>0.409708</td>\n",
       "      <td>0.666250</td>\n",
       "      <td>0.221404</td>\n",
       "      <td>5557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>718</th>\n",
       "      <td>719</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.332500</td>\n",
       "      <td>0.342162</td>\n",
       "      <td>0.625417</td>\n",
       "      <td>0.184092</td>\n",
       "      <td>5267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>719</th>\n",
       "      <td>720</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.330000</td>\n",
       "      <td>0.335217</td>\n",
       "      <td>0.667917</td>\n",
       "      <td>0.132463</td>\n",
       "      <td>4128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>720</th>\n",
       "      <td>721</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.326667</td>\n",
       "      <td>0.301767</td>\n",
       "      <td>0.556667</td>\n",
       "      <td>0.374383</td>\n",
       "      <td>3623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721</th>\n",
       "      <td>722</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.265833</td>\n",
       "      <td>0.236113</td>\n",
       "      <td>0.441250</td>\n",
       "      <td>0.407346</td>\n",
       "      <td>1749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>722</th>\n",
       "      <td>723</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.245833</td>\n",
       "      <td>0.259471</td>\n",
       "      <td>0.515417</td>\n",
       "      <td>0.133083</td>\n",
       "      <td>1787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>723</th>\n",
       "      <td>724</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.231304</td>\n",
       "      <td>0.258900</td>\n",
       "      <td>0.791304</td>\n",
       "      <td>0.077230</td>\n",
       "      <td>920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>724</th>\n",
       "      <td>725</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.291304</td>\n",
       "      <td>0.294465</td>\n",
       "      <td>0.734783</td>\n",
       "      <td>0.168726</td>\n",
       "      <td>1013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>726</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.243333</td>\n",
       "      <td>0.220333</td>\n",
       "      <td>0.823333</td>\n",
       "      <td>0.316546</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>726</th>\n",
       "      <td>727</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.254167</td>\n",
       "      <td>0.226642</td>\n",
       "      <td>0.652917</td>\n",
       "      <td>0.350133</td>\n",
       "      <td>2114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>728</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.253333</td>\n",
       "      <td>0.255046</td>\n",
       "      <td>0.590000</td>\n",
       "      <td>0.155471</td>\n",
       "      <td>3095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>729</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.253333</td>\n",
       "      <td>0.242400</td>\n",
       "      <td>0.752917</td>\n",
       "      <td>0.124383</td>\n",
       "      <td>1341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>729</th>\n",
       "      <td>730</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.255833</td>\n",
       "      <td>0.231700</td>\n",
       "      <td>0.483333</td>\n",
       "      <td>0.350754</td>\n",
       "      <td>1796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>730</th>\n",
       "      <td>731</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.215833</td>\n",
       "      <td>0.223487</td>\n",
       "      <td>0.577500</td>\n",
       "      <td>0.154846</td>\n",
       "      <td>2729</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>731 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     instant  season  yr  mnth  holiday  weekday  workingday  weathersit  \\\n",
       "0          1       1   0     1        0        6           0           2   \n",
       "1          2       1   0     1        0        0           0           2   \n",
       "2          3       1   0     1        0        1           1           1   \n",
       "3          4       1   0     1        0        2           1           1   \n",
       "4          5       1   0     1        0        3           1           1   \n",
       "5          6       1   0     1        0        4           1           1   \n",
       "6          7       1   0     1        0        5           1           2   \n",
       "7          8       1   0     1        0        6           0           2   \n",
       "8          9       1   0     1        0        0           0           1   \n",
       "9         10       1   0     1        0        1           1           1   \n",
       "10        11       1   0     1        0        2           1           2   \n",
       "11        12       1   0     1        0        3           1           1   \n",
       "12        13       1   0     1        0        4           1           1   \n",
       "13        14       1   0     1        0        5           1           1   \n",
       "14        15       1   0     1        0        6           0           2   \n",
       "15        16       1   0     1        0        0           0           1   \n",
       "16        17       1   0     1        1        1           0           2   \n",
       "17        18       1   0     1        0        2           1           2   \n",
       "18        19       1   0     1        0        3           1           2   \n",
       "19        20       1   0     1        0        4           1           2   \n",
       "20        21       1   0     1        0        5           1           1   \n",
       "21        22       1   0     1        0        6           0           1   \n",
       "22        23       1   0     1        0        0           0           1   \n",
       "23        24       1   0     1        0        1           1           1   \n",
       "24        25       1   0     1        0        2           1           2   \n",
       "25        26       1   0     1        0        3           1           3   \n",
       "26        27       1   0     1        0        4           1           1   \n",
       "27        28       1   0     1        0        5           1           2   \n",
       "28        29       1   0     1        0        6           0           1   \n",
       "29        30       1   0     1        0        0           0           1   \n",
       "..       ...     ...  ..   ...      ...      ...         ...         ...   \n",
       "701      702       4   1    12        0        0           0           2   \n",
       "702      703       4   1    12        0        1           1           1   \n",
       "703      704       4   1    12        0        2           1           1   \n",
       "704      705       4   1    12        0        3           1           1   \n",
       "705      706       4   1    12        0        4           1           1   \n",
       "706      707       4   1    12        0        5           1           2   \n",
       "707      708       4   1    12        0        6           0           2   \n",
       "708      709       4   1    12        0        0           0           2   \n",
       "709      710       4   1    12        0        1           1           2   \n",
       "710      711       4   1    12        0        2           1           2   \n",
       "711      712       4   1    12        0        3           1           2   \n",
       "712      713       4   1    12        0        4           1           1   \n",
       "713      714       4   1    12        0        5           1           1   \n",
       "714      715       4   1    12        0        6           0           1   \n",
       "715      716       4   1    12        0        0           0           2   \n",
       "716      717       4   1    12        0        1           1           2   \n",
       "717      718       4   1    12        0        2           1           1   \n",
       "718      719       4   1    12        0        3           1           1   \n",
       "719      720       4   1    12        0        4           1           2   \n",
       "720      721       1   1    12        0        5           1           2   \n",
       "721      722       1   1    12        0        6           0           1   \n",
       "722      723       1   1    12        0        0           0           1   \n",
       "723      724       1   1    12        0        1           1           2   \n",
       "724      725       1   1    12        1        2           0           2   \n",
       "725      726       1   1    12        0        3           1           3   \n",
       "726      727       1   1    12        0        4           1           2   \n",
       "727      728       1   1    12        0        5           1           2   \n",
       "728      729       1   1    12        0        6           0           2   \n",
       "729      730       1   1    12        0        0           0           1   \n",
       "730      731       1   1    12        0        1           1           2   \n",
       "\n",
       "         temp     atemp       hum  windspeed   cnt  \n",
       "0    0.344167  0.363625  0.805833   0.160446   985  \n",
       "1    0.363478  0.353739  0.696087   0.248539   801  \n",
       "2    0.196364  0.189405  0.437273   0.248309  1349  \n",
       "3    0.200000  0.212122  0.590435   0.160296  1562  \n",
       "4    0.226957  0.229270  0.436957   0.186900  1600  \n",
       "5    0.204348  0.233209  0.518261   0.089565  1606  \n",
       "6    0.196522  0.208839  0.498696   0.168726  1510  \n",
       "7    0.165000  0.162254  0.535833   0.266804   959  \n",
       "8    0.138333  0.116175  0.434167   0.361950   822  \n",
       "9    0.150833  0.150888  0.482917   0.223267  1321  \n",
       "10   0.169091  0.191464  0.686364   0.122132  1263  \n",
       "11   0.172727  0.160473  0.599545   0.304627  1162  \n",
       "12   0.165000  0.150883  0.470417   0.301000  1406  \n",
       "13   0.160870  0.188413  0.537826   0.126548  1421  \n",
       "14   0.233333  0.248112  0.498750   0.157963  1248  \n",
       "15   0.231667  0.234217  0.483750   0.188433  1204  \n",
       "16   0.175833  0.176771  0.537500   0.194017  1000  \n",
       "17   0.216667  0.232333  0.861667   0.146775   683  \n",
       "18   0.292174  0.298422  0.741739   0.208317  1650  \n",
       "19   0.261667  0.255050  0.538333   0.195904  1927  \n",
       "20   0.177500  0.157833  0.457083   0.353242  1543  \n",
       "21   0.059130  0.079070  0.400000   0.171970   981  \n",
       "22   0.096522  0.098839  0.436522   0.246600   986  \n",
       "23   0.097391  0.117930  0.491739   0.158330  1416  \n",
       "24   0.223478  0.234526  0.616957   0.129796  1985  \n",
       "25   0.217500  0.203600  0.862500   0.293850   506  \n",
       "26   0.195000  0.219700  0.687500   0.113837   431  \n",
       "27   0.203478  0.223317  0.793043   0.123300  1167  \n",
       "28   0.196522  0.212126  0.651739   0.145365  1098  \n",
       "29   0.216522  0.250322  0.722174   0.073983  1096  \n",
       "..        ...       ...       ...        ...   ...  \n",
       "701  0.347500  0.359208  0.823333   0.124379  4649  \n",
       "702  0.452500  0.455796  0.767500   0.082721  6234  \n",
       "703  0.475833  0.469054  0.733750   0.174129  6606  \n",
       "704  0.438333  0.428012  0.485000   0.324021  5729  \n",
       "705  0.255833  0.258204  0.508750   0.174754  5375  \n",
       "706  0.320833  0.321958  0.764167   0.130600  5008  \n",
       "707  0.381667  0.389508  0.911250   0.101379  5582  \n",
       "708  0.384167  0.390146  0.905417   0.157975  3228  \n",
       "709  0.435833  0.435575  0.925000   0.190308  5170  \n",
       "710  0.353333  0.338363  0.596667   0.296037  5501  \n",
       "711  0.297500  0.297338  0.538333   0.162937  5319  \n",
       "712  0.295833  0.294188  0.485833   0.174129  5532  \n",
       "713  0.281667  0.294192  0.642917   0.131229  5611  \n",
       "714  0.324167  0.338383  0.650417   0.106350  5047  \n",
       "715  0.362500  0.369938  0.838750   0.100742  3786  \n",
       "716  0.393333  0.401500  0.907083   0.098258  4585  \n",
       "717  0.410833  0.409708  0.666250   0.221404  5557  \n",
       "718  0.332500  0.342162  0.625417   0.184092  5267  \n",
       "719  0.330000  0.335217  0.667917   0.132463  4128  \n",
       "720  0.326667  0.301767  0.556667   0.374383  3623  \n",
       "721  0.265833  0.236113  0.441250   0.407346  1749  \n",
       "722  0.245833  0.259471  0.515417   0.133083  1787  \n",
       "723  0.231304  0.258900  0.791304   0.077230   920  \n",
       "724  0.291304  0.294465  0.734783   0.168726  1013  \n",
       "725  0.243333  0.220333  0.823333   0.316546   441  \n",
       "726  0.254167  0.226642  0.652917   0.350133  2114  \n",
       "727  0.253333  0.255046  0.590000   0.155471  3095  \n",
       "728  0.253333  0.242400  0.752917   0.124383  1341  \n",
       "729  0.255833  0.231700  0.483333   0.350754  1796  \n",
       "730  0.215833  0.223487  0.577500   0.154846  2729  \n",
       "\n",
       "[731 rows x 13 columns]"
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#CASUAL和REGISTERED同为预测值，根据作业要求先行剔除\n",
    "#可以将编号instant作为时间轴，dteday的大部分可利用信息都可以从其他参数上找到，由于只有一年的数据，也不适合作特征工程，这里舍弃作为OBJECT的dteday \n",
    "data1=data.drop(columns=['casual','registered','dteday'])\n",
    "data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(731, 13)"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#选取2011年数据作为训练数据，剔除yr=1的2012年数据\n",
    "#data2=data1.drop(columns='yr')\n",
    "data2=data1\n",
    "data2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mnth_1</th>\n",
       "      <th>mnth_2</th>\n",
       "      <th>mnth_3</th>\n",
       "      <th>mnth_4</th>\n",
       "      <th>mnth_5</th>\n",
       "      <th>mnth_6</th>\n",
       "      <th>mnth_7</th>\n",
       "      <th>mnth_8</th>\n",
       "      <th>mnth_9</th>\n",
       "      <th>mnth_10</th>\n",
       "      <th>...</th>\n",
       "      <th>weathersit_1</th>\n",
       "      <th>weathersit_2</th>\n",
       "      <th>weathersit_3</th>\n",
       "      <th>weekday_0</th>\n",
       "      <th>weekday_1</th>\n",
       "      <th>weekday_2</th>\n",
       "      <th>weekday_3</th>\n",
       "      <th>weekday_4</th>\n",
       "      <th>weekday_5</th>\n",
       "      <th>weekday_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   mnth_1  mnth_2  mnth_3  mnth_4  mnth_5  mnth_6  mnth_7  mnth_8  mnth_9  \\\n",
       "0       1       0       0       0       0       0       0       0       0   \n",
       "1       1       0       0       0       0       0       0       0       0   \n",
       "2       1       0       0       0       0       0       0       0       0   \n",
       "3       1       0       0       0       0       0       0       0       0   \n",
       "4       1       0       0       0       0       0       0       0       0   \n",
       "\n",
       "   mnth_10    ...      weathersit_1  weathersit_2  weathersit_3  weekday_0  \\\n",
       "0        0    ...                 0             1             0          0   \n",
       "1        0    ...                 0             1             0          1   \n",
       "2        0    ...                 1             0             0          0   \n",
       "3        0    ...                 1             0             0          0   \n",
       "4        0    ...                 1             0             0          0   \n",
       "\n",
       "   weekday_1  weekday_2  weekday_3  weekday_4  weekday_5  weekday_6  \n",
       "0          0          0          0          0          0          1  \n",
       "1          0          0          0          0          0          0  \n",
       "2          1          0          0          0          0          0  \n",
       "3          0          1          0          0          0          0  \n",
       "4          0          0          1          0          0          0  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features=['mnth','season','weathersit','weekday']\n",
    "x_train_cat=data2[categorical_features]\n",
    "x_train_cat=x_train_cat.astype(str)\n",
    "x_train_cat.dtypes\n",
    "x_train_cat=pd.get_dummies(x_train_cat)\n",
    "x_train_cat.to_csv(\"xtrain.csv\")\n",
    "#mnth_10仍是10月数据，但被get_dummies由字符顺序调到了mnth_1后面，强迫症患者需要调整列顺序\n",
    "x_train_cat=x_train_cat[['mnth_1',\n",
    " 'mnth_2',\n",
    " 'mnth_3',\n",
    " 'mnth_4',\n",
    " 'mnth_5',\n",
    " 'mnth_6',\n",
    " 'mnth_7',\n",
    " 'mnth_8',\n",
    " 'mnth_9',\n",
    " 'mnth_10',\n",
    " 'mnth_11',\n",
    " 'mnth_12',\n",
    " 'season_1',\n",
    " 'season_2',\n",
    " 'season_3',\n",
    " 'season_4',\n",
    " 'weathersit_1',\n",
    " 'weathersit_2',\n",
    " 'weathersit_3',\n",
    " 'weekday_0',\n",
    " 'weekday_1',\n",
    " 'weekday_2',\n",
    " 'weekday_3',\n",
    " 'weekday_4',\n",
    " 'weekday_5',\n",
    " 'weekday_6']]\n",
    "data3=pd.concat([x_train_cat,data2],axis=1)\n",
    "#data3.shape\n",
    "x_train_cat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mnth_1            uint8\n",
       "mnth_2            uint8\n",
       "mnth_3            uint8\n",
       "mnth_4            uint8\n",
       "mnth_5            uint8\n",
       "mnth_6            uint8\n",
       "mnth_7            uint8\n",
       "mnth_8            uint8\n",
       "mnth_9            uint8\n",
       "mnth_10           uint8\n",
       "mnth_11           uint8\n",
       "mnth_12           uint8\n",
       "season_1          uint8\n",
       "season_2          uint8\n",
       "season_3          uint8\n",
       "season_4          uint8\n",
       "weathersit_1      uint8\n",
       "weathersit_2      uint8\n",
       "weathersit_3      uint8\n",
       "weekday_0         uint8\n",
       "weekday_1         uint8\n",
       "weekday_2         uint8\n",
       "weekday_3         uint8\n",
       "weekday_4         uint8\n",
       "weekday_5         uint8\n",
       "weekday_6         uint8\n",
       "instant           int64\n",
       "yr                int64\n",
       "holiday           int64\n",
       "workingday        int64\n",
       "temp            float64\n",
       "atemp           float64\n",
       "hum             float64\n",
       "windspeed       float64\n",
       "cnt               int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4=data3.drop(columns=['season','mnth','weathersit','weekday'])\n",
    "data4.dtypes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 单变量分布分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2379768e358>]"
      ]
     },
     "execution_count": 299,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 租车量随时间变化\n",
    "fig = plt.figure()\n",
    "\n",
    "plt.plot(data.instant,data.cnt)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Y的直方图\n",
    "sns.distplot(data.cnt.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of rented bikes', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 单个特征散点图\n",
    "\n",
    "plt.scatter(range(data4.shape[0]), data4[\"temp\"],color='purple')\n",
    "plt.title(\"Temprature\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 输入属性的直方图／分布"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "湿度，温度等都经过了归一化处理，通过直方图未见超过MAX值的项，可以直接使用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.hum.values, bins=30, kde=False)\n",
    "plt.xlabel('Humidity', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FPtf9d7wCeOaE5DoOuK7b5gzg52Z7Ts9klaRGtTQGL0nqY8FLUqMseElqlAUvSY2y4CWpURa8JDXKgteiSfK9vq97k/ywb33EC9GPVze16/WLnUPakZEu2SeNoqr22LrcTTvwqqq6YPES/V+WXQCqamyzjibZtap2OI+INCr34DWxkixJ8idJNia5LcmHt06SleTR3YVbViX5dpLbk7wyya8n+XKSO5O8p++5TkpyYZL3Jrmru/jFk/ruvyTJKUkuBX4APDTJq5N8Ncnd3UUYXtltuy/wUeDhfX9x7JvkrCRv73vOn9nLT/KdJG9OcjVwV3fbwUnO636+jUlOGvPbqvsRC16T7A+BZwK/SW/ypZ/Sm0lyqyX0LuDycOAVwN/QzbjX3f6KJEf0bf8keqef7wucCvxbkr367n8Z8Lv0JjT7DnAL8Cx6c4OfBJye5LFVdTu9uWY2VtUe3dftA/5MLwGeAeybZAm96Wj/C3govTlj3prkyQM+l7RDFrwm2auBk6s3i96PgHcCL0nSP7XqKVX146pa161/sHqzOt5IrzgP69v2W1X1d9WbVfGD9OYl+q2++8+oqmu7+7dU1bqq+kb1XAD8B71fNqM4rft5ftg91+5V9a6q+klVfQ34J3qzK0ojcwxeE6kr8YOBjyfpnzBpF3p74AD3bLPn/EN6k7b1r+/Rt37TNi/zTXp7zlv1X3CBJMfQmwP/Ed3rPgj4z+F+kvvof42HAcu3uRbpEnqTz0kjs+A1kaqqknwbeEFVXbbt/UnmMj/3tpdCXMbPzrndf2GRB9O7BuZxwCeqakuST/L/F2aYaZa+79P7JbDVL8ywTf/jvgV8tap+ebD40nAcotEk+wfg1K2Xvkuyf5LnjvB8B3cftu7aXT1rGfCp7Wz7QOABwCbg3m5v/il9998K7J+k/y+EK4DnJNk7yUHMfqm3zwIkeUOS3btcj0vyK8P/aNJ9WfCaZO+mN1xxYZK76Y2pj1J+n6E3Jv9delfEeX5t54o4VXUbvQ9sP0bv2gHH0vtAdKsrgXXAN7sjdvYB3g9cD9wInM8sVymqqp/SmwP8N+gNF20G/p6fHVaS5sz54HW/0B1+eFxVPX2xs0gLxT14SWqUBS9JjXKIRpIa5R68JDXKgpekRlnwktQoC16SGmXBS1KjLHhJatT/An6AKdYLhFicAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.temp.values, bins=30, kde=False)\n",
    "plt.xlabel('Temprature', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.windspeed.values, bins=30, kde=False)\n",
    "plt.xlabel('Windspeed', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.workingday, order=[0, 1]);\n",
    "plt.xlabel('Working Days');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "天气条件里有4个级别，但第四类天气未出现，无法使用该特征对租车数量进行预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.weathersit)\n",
    "plt.xlabel('Weathersit', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 两两特征之间的相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [],
   "source": [
    "#get the names of all the columns\n",
    "cols=data4.columns \n",
    "\n",
    "# Calculates pearson co-efficient for all combinations，通常认为相关系数大于0.5的为强相关\n",
    "data_corr = data4.corr().abs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(35, 35)"
      ]
     },
     "execution_count": 308,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_corr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1872x1296 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(26, 18))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "\n",
    "# Mask unimportant features\n",
    "sns.heatmap(data_corr, mask=data_corr < 1, cbar=False)\n",
    "\n",
    "plt.savefig('bike.png' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "temp and atemp = 0.99\n",
      "weathersit_1 and weathersit_2 = 0.94\n",
      "instant and yr = 0.87\n",
      "season_3 and temp = 0.68\n",
      "season_3 and atemp = 0.66\n",
      "atemp and cnt = 0.63\n",
      "instant and cnt = 0.63\n",
      "temp and cnt = 0.63\n",
      "season_1 and atemp = 0.63\n",
      "season_1 and temp = 0.62\n",
      "weekday_0 and workingday = 0.60\n",
      "weekday_6 and workingday = 0.60\n",
      "weathersit_1 and hum = 0.58\n",
      "yr and cnt = 0.57\n",
      "season_1 and cnt = 0.56\n",
      "mnth_10 and season_4 = 0.54\n",
      "mnth_1 and season_1 = 0.53\n",
      "mnth_11 and season_4 = 0.53\n",
      "mnth_5 and season_2 = 0.52\n",
      "mnth_8 and season_3 = 0.52\n",
      "mnth_7 and season_3 = 0.52\n",
      "mnth_4 and season_2 = 0.52\n",
      "mnth_2 and season_1 = 0.51\n",
      "weathersit_2 and hum = 0.49\n",
      "mnth_1 and atemp = 0.44\n",
      "mnth_7 and temp = 0.43\n",
      "mnth_1 and temp = 0.43\n",
      "mnth_7 and atemp = 0.43\n",
      "mnth_1 and cnt = 0.37\n",
      "mnth_8 and temp = 0.35\n",
      "season_3 and cnt = 0.35\n",
      "season_4 and instant = 0.34\n",
      "season_2 and season_3 = 0.34\n",
      "season_1 and season_3 = 0.34\n",
      "season_3 and season_4 = 0.33\n",
      "season_1 and season_2 = 0.33\n",
      "mnth_8 and atemp = 0.33\n",
      "season_2 and season_4 = 0.33\n",
      "mnth_9 and season_3 = 0.33\n",
      "season_1 and season_4 = 0.33\n",
      "mnth_2 and temp = 0.31\n",
      "mnth_2 and atemp = 0.31\n",
      "mnth_6 and temp = 0.31\n",
      "mnth_6 and atemp = 0.30\n"
     ]
    }
   ],
   "source": [
    "#Set the threshold to select only highly correlated attributes\n",
    "threshold = 0.3\n",
    "# List of pairs along with correlation above threshold\n",
    "corr_list = []\n",
    "#size = data.shape[1]\n",
    "size = data_corr.shape[0]\n",
    "\n",
    "#Search for the highly correlated pairs\n",
    "for i in range(0, size): #for 'size' features\n",
    "    for j in range(i+1,size): #avoid repetition\n",
    "        if (data_corr.iloc[i,j] >= threshold and data_corr.iloc[i,j] < 1) or (data_corr.iloc[i,j] < 0 and data_corr.iloc[i,j] <= -threshold):\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j]) #store correlation and columns index\n",
    "\n",
    "#Sort to show higher ones first            \n",
    "s_corr_list = sorted(corr_list,key=lambda x: -abs(x[0]))\n",
    "\n",
    "#Print correlations and column names\n",
    "for v,i,j in s_corr_list:\n",
    "    print (\"%s and %s = %.2f\" % (cols[i],cols[j],v))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Scatter plot of only the highly correlated pairs\n",
    "#for v,i,j in s_corr_list:\n",
    "    #sns.pairplot(data4, size=6, x_vars=cols[i],y_vars=cols[j] )\n",
    "    #print(cols[i])\n",
    "    #plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(731, 34)"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#丢弃严格正相关的特征项\n",
    "data5=data4.drop(columns='atemp')\n",
    "data5.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.4 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 从原始数据中分离输入特征x和输出y\n",
    "y = data5['cnt'].values\n",
    "X = data5.drop('cnt', axis = 1)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面将训练数据分割成训练集和测试集，只是让大家对模型的训练误差、校验集上的测试误差估计、和测试集上的测试误差做个比较，实际任务中无需这么处理。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [],
   "source": [
    "#将数据分割训练数据与测试数据\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 取2012年的数据构建测试样本，其余作为训练样本\n",
    "X_train=X[X['yr']<1].drop(columns=['yr','instant'])\n",
    "X_test=X[X['yr']>0].drop(columns=['yr','instant'])\n",
    "y_train=y[0:365]\n",
    "y_test=y[365::]\n",
    "\n",
    "#用于后续显示权重系数对应的特征\n",
    "columns = X_train.columns\n",
    "\n",
    "#X_test, y_train, y_test = train_test_split(X, y, random_state=33, test_size=0.2)\n",
    "#X_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.5 数据预处理／特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2194.172782393892"
      ]
     },
     "execution_count": 318,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# 分别初始化对特征和目标值的标准化器\n",
    "#ss_X = StandardScaler()\n",
    "#ss_y = StandardScaler()\n",
    "\n",
    "# 分别对训练和测试数据的特征以及目标值进行标准化处理\n",
    "#X_train = ss_X.fit_transform(X_train)\n",
    "#X_test = ss_X.transform(X_test)\n",
    "#print(X_train.shape)\n",
    "\n",
    "#对y做标准化不是必须\n",
    "#对y标准化的好处是不同问题的w差异不太大，同时正则参数的范围也有限\n",
    "#y_train = ss_y.fit_transform(y_train.reshape(-1, 1))\n",
    "#y_test = ss_y.transform(y_test.reshape(-1, 1))\n",
    "bonus=y_test.mean()-y_train.mean()\n",
    "bonus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3、确定模型类型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 尝试缺省参数的线性回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>season_4</td>\n",
       "      <td>2.200063e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>season_3</td>\n",
       "      <td>2.200063e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>season_2</td>\n",
       "      <td>2.200063e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>season_1</td>\n",
       "      <td>2.200063e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>weathersit_1</td>\n",
       "      <td>1.744450e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>weathersit_2</td>\n",
       "      <td>1.744450e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>weathersit_3</td>\n",
       "      <td>1.744450e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>temp</td>\n",
       "      <td>3.057500e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>hum</td>\n",
       "      <td>-1.285500e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>-2.013664e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>weekday_2</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>weekday_5</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>weekday_1</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>weekday_3</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>weekday_4</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mnth_5</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mnth_6</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>mnth_9</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>mnth_4</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>mnth_10</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>mnth_8</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>mnth_11</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>mnth_12</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>mnth_7</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>mnth_3</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mnth_2</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>mnth_1</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>workingday</td>\n",
       "      <td>-2.767317e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>holiday</td>\n",
       "      <td>-2.767317e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>weekday_6</td>\n",
       "      <td>-2.957075e+16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>weekday_0</td>\n",
       "      <td>-2.957075e+16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         columns          coef\n",
       "15      season_4  2.200063e+16\n",
       "14      season_3  2.200063e+16\n",
       "13      season_2  2.200063e+16\n",
       "12      season_1  2.200063e+16\n",
       "16  weathersit_1  1.744450e+16\n",
       "17  weathersit_2  1.744450e+16\n",
       "18  weathersit_3  1.744450e+16\n",
       "28          temp  3.057500e+03\n",
       "29           hum -1.285500e+03\n",
       "30     windspeed -2.013664e+03\n",
       "21     weekday_2 -1.897586e+15\n",
       "24     weekday_5 -1.897586e+15\n",
       "20     weekday_1 -1.897586e+15\n",
       "22     weekday_3 -1.897586e+15\n",
       "23     weekday_4 -1.897586e+15\n",
       "4         mnth_5 -4.178248e+15\n",
       "5         mnth_6 -4.178248e+15\n",
       "8         mnth_9 -4.178248e+15\n",
       "3         mnth_4 -4.178248e+15\n",
       "9        mnth_10 -4.178248e+15\n",
       "7         mnth_8 -4.178248e+15\n",
       "10       mnth_11 -4.178248e+15\n",
       "11       mnth_12 -4.178248e+15\n",
       "6         mnth_7 -4.178248e+15\n",
       "2         mnth_3 -4.178248e+15\n",
       "1         mnth_2 -4.178248e+15\n",
       "0         mnth_1 -4.178248e+15\n",
       "27    workingday -2.767317e+16\n",
       "26       holiday -2.767317e+16\n",
       "25     weekday_6 -2.957075e+16\n",
       "19     weekday_0 -2.957075e+16"
      ]
     },
     "execution_count": 320,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 线性回归\n",
    "#class sklearn.linear_model.LinearRegression(fit_intercept=True, normalize=False, copy_X=True, n_jobs=1)\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "# 使用默认配置初始化\n",
    "lr = LinearRegression()\n",
    "\n",
    "# 训练模型参数\n",
    "lr.fit(X_train, y_train)\n",
    "\n",
    "# 预测\n",
    "y_test_pred_lr = lr.predict(X_test)+bonus\n",
    "y_train_pred_lr = lr.predict(X_train)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef\":list((lr.coef_.T))})\n",
    "fs.sort_values(by=['coef'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of LinearRegression on test is 0.6691332272600312\n",
      "The r2 score of LinearRegression on train is 0.8397317865958913\n"
     ]
    }
   ],
   "source": [
    "# 使用r2_score评价模型在测试集和训练集上的性能，并输出评估结果\n",
    "#测试集\n",
    "print('The r2 score of LinearRegression on test is', r2_score(y_test, y_test_pred_lr))\n",
    "#训练集\n",
    "print('The r2 score of LinearRegression on train is', r2_score(y_train, y_train_pred_lr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#在训练集上观察预测残差的分布，看是否符合模型假设：噪声为0均值的高斯噪声\n",
    "f, ax = plt.subplots(figsize=(7, 5)) \n",
    "f.tight_layout() \n",
    "ax.hist(y_train - y_train_pred_lr,bins=40, label='Residuals Linear', color='b', alpha=.5); \n",
    "ax.set_title(\"Histogram of Residuals\") \n",
    "ax.legend(loc='best');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "残差分布和高斯分布比较匹配，但还是左skew，可能是由于数据集中有16个数据的y值为最大值，有噪声（预测残差超过2.5）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#还可以观察预测值与真值的散点图\n",
    "plt.figure(figsize=(4, 3))\n",
    "plt.scatter(y_train, y_train_pred_lr)\n",
    "plt.plot([-3, 3], [-3, 3], '--k')   #数据已经标准化，3倍标准差即可\n",
    "plt.axis('tight')\n",
    "plt.xlabel('True price')\n",
    "plt.ylabel('Predicted price')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在y的真值大的部分预测效果不好"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-792.22863485, -584.18335318, -381.97409555,  154.87428194,\n",
       "       1004.2397748 ,  880.68788892,  170.74743948,  218.29739411,\n",
       "        568.05926772,  301.20575442, -160.90805048, -238.05776084,\n",
       "       -347.03167824,  123.76516619,  532.88930071,  831.13711782,\n",
       "       1130.52980832,  731.08858758, -720.85848942,  312.41806538,\n",
       "         62.22355203,  115.51488519,   51.95633234,   39.32079554,\n",
       "        105.91012287,  453.41615314,    5.17466886,  369.7510191 ,\n",
       "       2307.6232712 , -669.36094555, -877.43026966])"
      ]
     },
     "execution_count": 326,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 线性模型，随机梯度下降优化模型参数\n",
    "# 随机梯度下降一般在大数据集上应用，其实本项目不适合用\n",
    "from sklearn.linear_model import SGDRegressor\n",
    "\n",
    "# 使用默认配置初始化线\n",
    "sgdr = SGDRegressor(max_iter=1000)\n",
    "\n",
    "# 训练：参数估计\n",
    "sgdr.fit(X_train, y_train)\n",
    "\n",
    "# 预测\n",
    "sgdr_y_predict = sgdr.predict(X_test)+bonus\n",
    "\n",
    "sgdr.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The value of default measurement of SGDRegressor on test is -0.7135281331664889\n",
      "The value of default measurement of SGDRegressor on train is 0.836063548146232\n"
     ]
    }
   ],
   "source": [
    "# 使用SGDRegressor模型自带的评估模块(评价准则为r2_score)，并输出评估结果\n",
    "print ('The value of default measurement of SGDRegressor on test is', sgdr.score(X_test, y_test))\n",
    "print ('The value of default measurement of SGDRegressor on train is', sgdr.score(X_train, y_train))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#这里由于样本数不多，SGDRegressor可能不如LinearRegression。 sklearn建议样本数超过10万采用SGDRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 正则化的线性回归（L2正则 --> 岭回归）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of RidgeCV on test is 0.6649764791938388\n",
      "The r2 score of RidgeCV on train is 0.8407236861266663\n"
     ]
    }
   ],
   "source": [
    "#岭回归／L2正则\n",
    "#class sklearn.linear_model.RidgeCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, \n",
    "#                                  normalize=False, scoring=None, cv=None, gcv_mode=None, \n",
    "#                                  store_cv_values=False)\n",
    "from sklearn.linear_model import  RidgeCV\n",
    "\n",
    "#设置超参数（正则参数）范围\n",
    "alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "#n_alphas = 20\n",
    "#alphas = np.logspace(-5,2,n_alphas)\n",
    "\n",
    "#生成一个RidgeCV实例\n",
    "ridge = RidgeCV(alphas=alphas, store_cv_values=True)  \n",
    "\n",
    "#模型训练\n",
    "ridge.fit(X_train, y_train)    \n",
    "\n",
    "#预测\n",
    "y_test_pred_ridge = ridge.predict(X_test)+bonus\n",
    "y_train_pred_ridge = ridge.predict(X_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print('The r2 score of RidgeCV on test is', r2_score(y_test, y_test_pred_ridge))\n",
    "print('The r2 score of RidgeCV on train is', r2_score(y_train, y_train_pred_ridge))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 0.1\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef_lr</th>\n",
       "      <th>coef_ridge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>season_4</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>542.674394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>season_3</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>247.692144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>season_2</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>-175.311138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>season_1</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>-615.055400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>weathersit_1</td>\n",
       "      <td>1.744450e+16</td>\n",
       "      <td>646.139994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>weathersit_2</td>\n",
       "      <td>1.744450e+16</td>\n",
       "      <td>342.058285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>weathersit_3</td>\n",
       "      <td>1.744450e+16</td>\n",
       "      <td>-988.198278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>temp</td>\n",
       "      <td>3.057500e+03</td>\n",
       "      <td>2933.518127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>hum</td>\n",
       "      <td>-1.285500e+03</td>\n",
       "      <td>-1224.936019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>-2.013664e+03</td>\n",
       "      <td>-1863.089951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>weekday_2</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>6.375397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>weekday_5</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>8.130920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>weekday_1</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>-35.246998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>weekday_3</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>-40.487469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>weekday_4</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>-62.278769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mnth_5</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>902.050731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mnth_6</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>631.743061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>mnth_9</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>403.022285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>mnth_4</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>143.267606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>mnth_10</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>224.070857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>mnth_8</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-9.088370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>mnth_11</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-195.504996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>mnth_12</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-257.399193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>mnth_7</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-120.665690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>mnth_3</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-395.425476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mnth_2</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-568.205995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>mnth_1</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-757.864820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>workingday</td>\n",
       "      <td>-2.767317e+16</td>\n",
       "      <td>131.174591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>holiday</td>\n",
       "      <td>-2.767317e+16</td>\n",
       "      <td>-254.681509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>weekday_6</td>\n",
       "      <td>-2.957075e+16</td>\n",
       "      <td>131.662206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>weekday_0</td>\n",
       "      <td>-2.957075e+16</td>\n",
       "      <td>-8.155287</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         columns       coef_lr   coef_ridge\n",
       "15      season_4  2.200063e+16   542.674394\n",
       "14      season_3  2.200063e+16   247.692144\n",
       "13      season_2  2.200063e+16  -175.311138\n",
       "12      season_1  2.200063e+16  -615.055400\n",
       "16  weathersit_1  1.744450e+16   646.139994\n",
       "17  weathersit_2  1.744450e+16   342.058285\n",
       "18  weathersit_3  1.744450e+16  -988.198278\n",
       "28          temp  3.057500e+03  2933.518127\n",
       "29           hum -1.285500e+03 -1224.936019\n",
       "30     windspeed -2.013664e+03 -1863.089951\n",
       "21     weekday_2 -1.897586e+15     6.375397\n",
       "24     weekday_5 -1.897586e+15     8.130920\n",
       "20     weekday_1 -1.897586e+15   -35.246998\n",
       "22     weekday_3 -1.897586e+15   -40.487469\n",
       "23     weekday_4 -1.897586e+15   -62.278769\n",
       "4         mnth_5 -4.178248e+15   902.050731\n",
       "5         mnth_6 -4.178248e+15   631.743061\n",
       "8         mnth_9 -4.178248e+15   403.022285\n",
       "3         mnth_4 -4.178248e+15   143.267606\n",
       "9        mnth_10 -4.178248e+15   224.070857\n",
       "7         mnth_8 -4.178248e+15    -9.088370\n",
       "10       mnth_11 -4.178248e+15  -195.504996\n",
       "11       mnth_12 -4.178248e+15  -257.399193\n",
       "6         mnth_7 -4.178248e+15  -120.665690\n",
       "2         mnth_3 -4.178248e+15  -395.425476\n",
       "1         mnth_2 -4.178248e+15  -568.205995\n",
       "0         mnth_1 -4.178248e+15  -757.864820\n",
       "27    workingday -2.767317e+16   131.174591\n",
       "26       holiday -2.767317e+16  -254.681509\n",
       "25     weekday_6 -2.957075e+16   131.662206\n",
       "19     weekday_0 -2.957075e+16    -8.155287"
      ]
     },
     "execution_count": 330,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mse_mean = np.mean(ridge.cv_values_, axis = 0)\n",
    "plt.plot(np.log10(alphas), mse_mean.reshape(len(alphas),1)) \n",
    "\n",
    "#这是为了标出最佳参数的位置，不是必须\n",
    "#plt.plot(np.log10(ridge.alpha_)*np.ones(3), [0.28, 0.29, 0.30])\n",
    "\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()\n",
    "\n",
    "print ('alpha is:', ridge.alpha_)\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef_lr\":list((lr.coef_.T)), \"coef_ridge\":list((ridge.coef_.T))})\n",
    "fs.sort_values(by=['coef_lr'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 正则化的线性回归（L1正则 --> Lasso）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of LassoCV on test is 0.6658249335320446\n",
      "The r2 score of LassoCV on train is 0.840602538713229\n"
     ]
    }
   ],
   "source": [
    "#### Lasso／L1正则\n",
    "# class sklearn.linear_model.LassoCV(eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, \n",
    "#                                    normalize=False, precompute=’auto’, max_iter=1000, \n",
    "#                                    tol=0.0001, copy_X=True, cv=None, verbose=False, n_jobs=1,\n",
    "#                                    positive=False, random_state=None, selection=’cyclic’)\n",
    "from sklearn.linear_model import LassoCV\n",
    "\n",
    "#设置超参数搜索范围\n",
    "#alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "\n",
    "#生成一个LassoCV实例\n",
    "#lasso = LassoCV(alphas=alphas)  \n",
    "lasso = LassoCV()  \n",
    "\n",
    "#训练（内含CV）\n",
    "lasso.fit(X_train, y_train)  \n",
    "\n",
    "#测试\n",
    "y_test_pred_lasso = lasso.predict(X_test)+bonus\n",
    "y_train_pred_lasso = lasso.predict(X_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print('The r2 score of LassoCV on test is', r2_score(y_test, y_test_pred_lasso))\n",
    "print('The r2 score of LassoCV on train is', r2_score(y_train, y_train_pred_lasso))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 0.65176513893046\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef_lr</th>\n",
       "      <th>coef_ridge</th>\n",
       "      <th>coef_lasso</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>season_4</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>542.674394</td>\n",
       "      <td>277.922423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>season_3</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>247.692144</td>\n",
       "      <td>16.689413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>season_2</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>-175.311138</td>\n",
       "      <td>-370.372767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>season_1</td>\n",
       "      <td>2.200063e+16</td>\n",
       "      <td>-615.055400</td>\n",
       "      <td>-875.549391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>weathersit_1</td>\n",
       "      <td>1.744450e+16</td>\n",
       "      <td>646.139994</td>\n",
       "      <td>305.068257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>weathersit_2</td>\n",
       "      <td>1.744450e+16</td>\n",
       "      <td>342.058285</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>weathersit_3</td>\n",
       "      <td>1.744450e+16</td>\n",
       "      <td>-988.198278</td>\n",
       "      <td>-1329.649114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>temp</td>\n",
       "      <td>3.057500e+03</td>\n",
       "      <td>2933.518127</td>\n",
       "      <td>3092.117681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>hum</td>\n",
       "      <td>-1.285500e+03</td>\n",
       "      <td>-1224.936019</td>\n",
       "      <td>-1200.135137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>-2.013664e+03</td>\n",
       "      <td>-1863.089951</td>\n",
       "      <td>-1846.543711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>weekday_2</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>6.375397</td>\n",
       "      <td>39.369685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>weekday_5</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>8.130920</td>\n",
       "      <td>46.212842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>weekday_1</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>-35.246998</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>weekday_3</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>-40.487469</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>weekday_4</td>\n",
       "      <td>-1.897586e+15</td>\n",
       "      <td>-62.278769</td>\n",
       "      <td>-18.900089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mnth_5</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>902.050731</td>\n",
       "      <td>894.914671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mnth_6</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>631.743061</td>\n",
       "      <td>620.514675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>mnth_9</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>403.022285</td>\n",
       "      <td>432.067032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>mnth_4</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>143.267606</td>\n",
       "      <td>150.335497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>mnth_10</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>224.070857</td>\n",
       "      <td>301.507220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>mnth_8</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-9.088370</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>mnth_11</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-195.504996</td>\n",
       "      <td>-93.020710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>mnth_12</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-257.399193</td>\n",
       "      <td>-143.258222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>mnth_7</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-120.665690</td>\n",
       "      <td>-105.724512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>mnth_3</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-395.425476</td>\n",
       "      <td>-307.063830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mnth_2</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-568.205995</td>\n",
       "      <td>-449.360706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>mnth_1</td>\n",
       "      <td>-4.178248e+15</td>\n",
       "      <td>-757.864820</td>\n",
       "      <td>-626.763735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>workingday</td>\n",
       "      <td>-2.767317e+16</td>\n",
       "      <td>131.174591</td>\n",
       "      <td>15.696785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>holiday</td>\n",
       "      <td>-2.767317e+16</td>\n",
       "      <td>-254.681509</td>\n",
       "      <td>-349.521377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>weekday_6</td>\n",
       "      <td>-2.957075e+16</td>\n",
       "      <td>131.662206</td>\n",
       "      <td>54.347790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>weekday_0</td>\n",
       "      <td>-2.957075e+16</td>\n",
       "      <td>-8.155287</td>\n",
       "      <td>-78.506656</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         columns       coef_lr   coef_ridge   coef_lasso\n",
       "15      season_4  2.200063e+16   542.674394   277.922423\n",
       "14      season_3  2.200063e+16   247.692144    16.689413\n",
       "13      season_2  2.200063e+16  -175.311138  -370.372767\n",
       "12      season_1  2.200063e+16  -615.055400  -875.549391\n",
       "16  weathersit_1  1.744450e+16   646.139994   305.068257\n",
       "17  weathersit_2  1.744450e+16   342.058285     0.000000\n",
       "18  weathersit_3  1.744450e+16  -988.198278 -1329.649114\n",
       "28          temp  3.057500e+03  2933.518127  3092.117681\n",
       "29           hum -1.285500e+03 -1224.936019 -1200.135137\n",
       "30     windspeed -2.013664e+03 -1863.089951 -1846.543711\n",
       "21     weekday_2 -1.897586e+15     6.375397    39.369685\n",
       "24     weekday_5 -1.897586e+15     8.130920    46.212842\n",
       "20     weekday_1 -1.897586e+15   -35.246998    -0.000000\n",
       "22     weekday_3 -1.897586e+15   -40.487469    -0.000000\n",
       "23     weekday_4 -1.897586e+15   -62.278769   -18.900089\n",
       "4         mnth_5 -4.178248e+15   902.050731   894.914671\n",
       "5         mnth_6 -4.178248e+15   631.743061   620.514675\n",
       "8         mnth_9 -4.178248e+15   403.022285   432.067032\n",
       "3         mnth_4 -4.178248e+15   143.267606   150.335497\n",
       "9        mnth_10 -4.178248e+15   224.070857   301.507220\n",
       "7         mnth_8 -4.178248e+15    -9.088370     0.000000\n",
       "10       mnth_11 -4.178248e+15  -195.504996   -93.020710\n",
       "11       mnth_12 -4.178248e+15  -257.399193  -143.258222\n",
       "6         mnth_7 -4.178248e+15  -120.665690  -105.724512\n",
       "2         mnth_3 -4.178248e+15  -395.425476  -307.063830\n",
       "1         mnth_2 -4.178248e+15  -568.205995  -449.360706\n",
       "0         mnth_1 -4.178248e+15  -757.864820  -626.763735\n",
       "27    workingday -2.767317e+16   131.174591    15.696785\n",
       "26       holiday -2.767317e+16  -254.681509  -349.521377\n",
       "25     weekday_6 -2.957075e+16   131.662206    54.347790\n",
       "19     weekday_0 -2.957075e+16    -8.155287   -78.506656"
      ]
     },
     "execution_count": 332,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()    \n",
    "            \n",
    "print ('alpha is:', lasso.alpha_)\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef_lr\":list((lr.coef_.T)), \"coef_ridge\":list((ridge.coef_.T)), \"coef_lasso\":list((lasso.coef_.T))})\n",
    "fs.sort_values(by=['coef_lr'],ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 0.65176513893046\n"
     ]
    }
   ],
   "source": [
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()    \n",
    "            \n",
    "print ('alpha is:', lasso.alpha_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
